The Senescence Associated Secretory Phenotype, a key marker of cellular senescence, is elevated in depression and moderated by sex
Bibliographic record
Abstract
OBJECTIVE: Studies have found elevation in a key biomarker of aging (the senescence-associated secretory phenotype (SASP) index) in depression. We investigated whether sex moderates the association between the SASP and major depression in older adults. METHODS: We included 423 older adults in a current major depressive episode and 140 adults with no history of depression. We measured the plasma levels of SASP biomarkers using multiplex immunoassays. The interaction effect between sex, depression diagnosis, and senescence markers were analyzed by general linear models, adjusted for confounding variables. RESULTS: Individuals with depression had a higher SASP index than the healthy comparison group (t-test= -3.902, p < 0.001). We found a significant diagnosis by sex interaction (F= 9.112, df= 1540, p = 0.003), with males with depression having the highest SASP index levels (F=20.678, df=1540, p < 0.001). CONCLUSIONS: In older adults, sex plays a significant role in senescence-related changes in depression. A higher senescence burden in males with depression may be an indicator of greater vulnerability to accelerated biological aging and a marker of elevated risk of adverse outcomes in this sex.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".